The ability to rapidly detect and quantify specific proteins in a highly multiplexed manner is of great importance for basic science research, drug screening applications, and clinical diagnosis. In this application we propose the development of a novel methodology which will allow generation of reporter molecules capable at the same time to recognize and to signal the recognition of a specific protein molecule. The signal generated by these "molecular beacons" will be simple to measure fluorescence intensity, which will facilitate high-throughput use of this new methodology. The proposed method will allow design of truly homogenous assays. This methodology will be initially developed for proteins having natural sequence specific DNA binding activity. Subsequently, this methodology will be expanded to include the proteins which do not possess natural sequence specific nucleic acid binding activity. There will be two phases of this project. In the first phase we will use the model protein systems to provide "proof of principle" evidence that our approach can be developed for a DNA-binding protein and that it can be expanded to proteins lacking such activity. In the second phase of the project we will apply the concepts developed in the first phase of the project to generate "molecular beacons" which will recognize four cancer-related targets: p53 - a tumor suppressor whose inactivation is the most common defect in cancer cells, NF-kB - transcription factor involved in regulation of many genes and found to be constitutively active in many tumors, p16(INK4A) - a tumor suppressor involved in cell cycle regulation whose mutations have been found in greater than 70 different types of tumor cells, and p27(Kip1) - a cell-cycle inhibitor whose cellular levels were shown to be an important prognostic marker in breast cancer patients. We expect that the methodology we propose to develop will find broad applications in basic cancer research, molecular diagnosis of disease, identification of therapeutic markers and targets, and in characterization of response to pharmaceuticals.